摘要
论文主要阐述了一种基于数据聚类的目标检测方法,该方法将数据点间的距离关系作为聚类分析的依据,通过对数据的聚类分析得到目标的位置和外形尺寸。该算法有着广泛的应用,不但可以应用于激光雷达点云数据的处理,还可以应用于图像数据的处理,实验结果表明该算法正确有效。
An algorithm about target detection based on data clustering is proposed,the algorithm is on the basis of the distance between each data,the position and boundary dimension of target is obtained through the analysis of the data clustering. The algorithm is extensive used not only in point cloud data of laser-scanner handling,but also in image data processing,the validity and effectiveness of the algorithm is proved by experiment.
出处
《机电产品开发与创新》
2016年第6期7-9,共3页
Development & Innovation of Machinery & Electrical Products
关键词
数据聚类
目标检测
data clustering
target detection
